The advent of autonomous regional satellite based navigation systems has enabled some countries to cover their territorial footprint and the footprint of their surrounding areas. The purpose of a regional satellite based navigation system, for example, the Indian regional navigational satellite system (IRNSS), is to cater to the needs of specific users, for example, military personnel for military applications using a precision service (PS), and civilian users for civilian applications using a standard positioning service (SPS).
A number of issues need to be addressed in the design of a satellite navigation system, for example, sensitivity improvements, jamming margins, robustness towards spoofing, cross correlation detection, multipath related improvements, time to first fix (TTFF), etc., for ensuring the efficiency and robustness of the satellite navigation system. Cross correlation is a measure of agreement of two signals. Each satellite of a global positioning system (GPS) transmits a unique pseudorandom noise (PRN) code that does not correlate well with the PRN code of another satellite. In a global navigation satellite system (GNSS) receiver, correlation values are continuously compared against a threshold above which the GNSS receiver is used for subsequent operations. For example, measurement validity and tracking limits are typically compared against a specific carrier to noise density (C/No) ratio based on the category of the receiver. Typically, this threshold is kept as low as possible to effectively obtain a satellite signal.
Consider an example where a receiver tracks two satellites of a global positioning system (GPS) that transmit two pseudorandom noise (PRN) codes, for example, PRN-1 and PRN-2 respectively. One PRN code signal has a higher signal strength with respect to the other PRN code signal. In this example, PRN-1 is assumed at the lowest possible value and the PRN-2 is assumed at the extreme maximum permissible value within the dynamic range of the receiver. If the absolute difference in the signal strength for this pair of satellites exceeds the typical 22 decibel (dB) margin, the satellite that transmits PRN-1 will not be able to effectively discriminate itself from the satellite that transmits PRN-2, and thus the receiver starts to falsely track the satellite that transmits PRN-2 instead of tracking the satellite that transmits PRN-1. With false lock and navigation data continuously failing the integrity checks, for example, a cyclic redundancy check (CRC) or a parity check, the satellite channel is reset and the processing is attempted again. However, if the navigation data passes the integrity checks effectively, the satellite that transmits PRN-1 effectively will be tracking the data of the satellite that transmits PRN-2.
The individual signals from each satellite as observed at a user antenna is given, for example, by:y1(t)=A1r1(t)d1(t)cos(2πf1t)y2(t)=A2r2(t)d2(t)cos(2πf1t)
where A is the received amplitude, r(t) is the ranging code, d(t) is the navigation data transmitted by the satellites, and f1 is the center frequency of the transmitted signal. The GNSS satellite antenna design ensures that the received signals from a user's local zenith or horizon are nearly the same to compensate for range variations. A1 and A2 vary due to a local phenomenon, for example, when the receiver obtains a direct and a reflected signal. The differential power level for a satellite pair exceeding 22 dB results in cross correlation. Under such a scenario within the receiver, the cross correlation on y1(t) results in a false tracking of y2(t) and as a fallout,d2(t)=d1(t)
To counter the above phenomenon, range differencing is adopted in civil aviation applications, which assumes the availability of almanac data, position, and time to detect a cross correlated signal. However, the detection of the cross correlated signal is not instantaneous, for example, at the data processing level.
Hence, there is a long felt but unresolved need for a method and a system that detect cross correlation within a frame of navigation data in real time and which obviate the dependence on almanac data from satellites for real time applications.